U.S. patent application number 12/501805 was filed with the patent office on 2010-01-14 for calculating connectivity, social proximity and trust level between web user.
This patent application is currently assigned to TROS INTERACTIVE LTD.. Invention is credited to Tuvia ROSENTHAL, Erel SEGAL, Erez SEGAL.
Application Number | 20100010826 12/501805 |
Document ID | / |
Family ID | 41505950 |
Filed Date | 2010-01-14 |
United States Patent
Application |
20100010826 |
Kind Code |
A1 |
ROSENTHAL; Tuvia ; et
al. |
January 14, 2010 |
CALCULATING CONNECTIVITY, SOCIAL PROXIMITY AND TRUST LEVEL BETWEEN
WEB USER
Abstract
A computer implemented system for, and a computer implemented
method of calculating indicators to reflect real-life interactions
between people, among those are connectivity, social proximity,
best paths and trust level. The system comprises a server connected
via a communication link to users associated with communication and
web based environments and to the web based environments and
communication platforms themselves. The server is arranged to
receive data relating to users, their profiles, connections and
related data in the communication and web based environments as
well as large scale data from these environments. The server
comprises an application arranged to convert the data into a
standard numeric format quantifying the connectivity, the social
proximity, the trust level and other indicators to reflect
real-life interactions between people. The computer implemented
method collects information about the users and their connectivity,
and analyses and maps the information as a virtual network spanning
a plurality of the web based environments and communication
platforms.
Inventors: |
ROSENTHAL; Tuvia;
(Herzeliya, IL) ; SEGAL; Erel; (Kiryat Haim,
IL) ; SEGAL; Erez; (Kiryat Haim, IL) |
Correspondence
Address: |
The Law Office of Michael E. Kondoudis
888 16th Street, N.W., Suite 800
Washington
DC
20006
US
|
Assignee: |
TROS INTERACTIVE LTD.
Herzeliya
IL
|
Family ID: |
41505950 |
Appl. No.: |
12/501805 |
Filed: |
July 13, 2009 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61080254 |
Jul 13, 2008 |
|
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Current U.S.
Class: |
705/1.1 |
Current CPC
Class: |
G06Q 99/00 20130101 |
Class at
Publication: |
705/1 |
International
Class: |
G06Q 99/00 20060101
G06Q099/00 |
Claims
1. A data processing system for calculating connectivity, social
proximity and trust level in social networks, the data processing
system comprising: a server comprising an application, a graphical
user interface and a database, the server connected via a
communication link to a plurality of users operatively associated
with a social layer comprising at least one web based social
environment, and the server further connected via the communication
link to the at least one web based social environments, wherein the
users have profiles, connection and related data in the web based
social environments, wherein the server is arranged to receive data
relating to the users, their profiles, connections and related data
in the web based social environments as well as large scale data
from the web based social environments, and wherein the application
is arranged to convert the data into a standard numeric format
quantifying the connectivity, the social proximity and the trust
level in the social networks.
2. The data processing system of claim 1, wherein the user
interface is arranged to allow users to input acquaintance data
relating to them and other users.
3. The data processing system of claim 1, wherein the application
is further arranged to authenticate user identities.
4. The data processing system of claim 1, wherein the application
is further arranged to rate user credibility in a context of
electronic commerce from the calculated measures in respect to
other users.
5. The data processing system of claim 1, wherein the data is
collected from social networking sites, websites, instant messaging
applications, chat applications, email applications, mobile
applications, MMS, SMS, and TV broadcasting channels.
6. The data processing system of claim 1, wherein the server
comprises an online module arranged to update the data and related
calculations substantially immediately after information changes,
and an offline module arranged to analyze the data and derived
measures.
7. A computer implemented method of calculating connectivity,
social proximity and trust level in social networks, the method
comprising: collecting information related to users operatively
associated with a social layer comprising at least one web based
social environment; collecting acquaintance data relating to users
of the social layer; converting the acquaintance data into a
standard numeric format; calculating measures for connected users
of the social layer; generating at least one connection graph , a
plurality of paths and at least one subjective network relating to
the users of the social layer; adding information to the subjective
networks; calculating measures for non connected users of the
social layer; generating a virtual network spanning a plurality of
the web based social environments; and upon query--responding to
the query by using the subjective networks and caching calculated
measures.
8. The computer implemented method of claim 7, further comprising
authenticating user identities by crossing the collected
information from various sources.
9. The computer implemented method of claim 7, further comprising
rating user credibility in a content of electronic commerce from
the calculated measures in respect to other users.
10. The computer implemented method of claim 7, wherein the
information is collected from social networking sites, websites,
instant messaging applications, chat applications, email
applications, mobile applications, MMS, SMS, and TV broadcasting
channels.
11. The computer implemented method of claim 7, wherein the
calculating measures for connected users of the social layer is
carried out pair wise.
12. The computer implemented method of claim 7, wherein the
collected information comprises measures relating to a single
user.
13. The computer implemented method of claim 12, wherein the
measures relating to a single user comprise a user's social
connectivity.
14. The computer implemented method of claim 7, further comprising
updating the collected information and related calculations
substantially immediately after information changes.
15. The computer implemented method of claim 7, wherein calculating
measures for connected users comprises an approximate number of
interactions between the connected users, the duration of their
relationship, and the nature of their interactions.
16. The computer implemented method of claim 7, wherein collecting
information related to users comprises questioning users for
acquaintance data relating to other users.
17. The computer implemented method of claim 7, wherein collecting
information related to users comprises collecting communication
patterns of users as registered in communication utilities.
18. The computer implemented method of claim 7, further comprising
assigning predefined connection strengths to predefined
relationships between users in predefined organizations.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Patent Application 61/080,254 filed on Jul. 13, 2008, which is
incorporated herein by reference.
BACKGROUND
[0002] 1. Technical Field
[0003] The present invention relates to the field of internet
applications, and more particularly, to social networks and web
based applications where users interact.
[0004] 2. Discussion of Related Art
[0005] With the rise in social network usage, and increase
interaction between users over the internet, the problem of
communicating/interacting with a virtual stranger and finding
trustable partners for dating, business or other social goals
becomes more and more important. Social networks have a vast
potential for creating new relationships between people, but the
problems of fake identities and scammers cause distrust and block
that potential from achieving full realization.
[0006] U.S. Patent Publication No. 20050197846, which is
incorporated herein by reference in its entirety, discloses a
method and system for generating a proximity index in a social
networking environment, in which a first user defines relationships
with a plurality of second users by assigning a relationship
designator for each connection of a relationship. The first user
stores content within the social networking environment and denotes
individuals allowed to or prevented from accessing the content by
entering one or more proximity thresholds. The social networking
environment may generate a proximity index based on a variety of
factors. The proximity index may be assigned a particular proximity
index grouping depending upon a range in which a proximity index
lies. The first user may control access to content and/or allow or
prevent the reception and/or display of content from other users
based on the other users' proximity index or proximity index
grouping with respect to the first user. The user may further order
a contact list based on proximity thresholds.
[0007] U.S. Patent Publication No. 20060149708, which is
incorporated herein by reference in its entirety, discloses a
search method and system using the same information regarding the
structure of information in a content database is maintained in a
structure database. The structure database is used to correlate the
data structure of a query to the structure of the content database,
in order to determine that information in the content database
which needs to be provided to a searcher in response to the query.
In one embodiment, this search method is used in an online forum,
and the forum maintains a reputation score for users with respect
to given subject matter. The reputation score is dependent upon the
quality of a user's participation in the forum. A user's reputation
score depends upon the evaluation by others of information he posts
and upon the user evaluating information posted by others.
BRIEF SUMMARY
[0008] Embodiments of the present invention provide a computer
implemented system for calculating connectivity, social proximity,
trust level, best social paths and other indications between people
using internet and communication platforms. One system comprises a
server connected via a communication link to a plurality of users
operatively associated with a social layer comprising at least one
web based social environment and to at least one web based social
environment or communication environment. The server comprises an
application, a graphical user interface and a database, and is
arranged to receive data relating to users, their profiles,
connection and related data in the web based social environments as
well as large scale data from the web based social environments.
The application is arranged to convert the data into a standard
numeric format quantifying the connectivity, the social proximity
and the trust level in the social networks.
[0009] Embodiments of the present invention provide a computer
implemented method of calculating connectivity, social proximity,
best paths and trust level in social networks. One method comprises
the stages: (i) collecting information related to users operatively
associated with a social layer comprising at least one web based
social environment, (ii) collecting acquaintance data relating to
users of the social layer, (iii) converting the acquaintance data
into a standard numeric format, (iv) calculating measures for
connected users of the social layer, (v) generating at least one
connection graph, a plurality of paths and at least one subjective
network relating to the users of the social layer, (vi) adding
information to the subjective networks, (vii) calculating measures
for non connected users of the social layer, (viii) generating a
virtual network spanning a plurality of the web based social
environments, and (ix) upon query--responding to the query by using
the subjective networks and caching calculated measures.
[0010] These, additional, and/or other aspects and/or advantages of
the present invention are: set forth in the detailed description
which follows; possibly inferable from the detailed description;
and/or learnable by practice of the present invention.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The present invention will be more readily understood from
the detailed description of embodiments thereof made in conjunction
with the accompanying drawings of which:
[0012] FIG. 1 is a high level schematic block diagram illustrating
a data processing system for calculating connectivity, social
proximity and trust level in social networks, according to some
embodiments of the invention; and
[0013] FIGS. 2 and 3 are high level flowcharts illustrating a
computer implemented method of calculating connectivity, social
proximity and trust level in social networks, according to some
embodiments of the invention.
DETAILED DESCRIPTION
[0014] Before explaining at least one embodiment of the invention
in detail, it is to be understood that the invention is not limited
in its application to the details of construction and the
arrangement of the components set forth in the following
description or illustrated in the drawings. The invention is
applicable to other embodiments or of being practiced or carried
out in various ways. Also, it is to be understood that the
phraseology and terminology employed herein is for the purpose of
description and should not be regarded as limiting.
[0015] Embodiments of the present invention disclose a method and
system for aggregating connectivity between users from various
sources and creating a repository of the information in order to
facilitate the calculation and measurement of some measures between
any two users in the net. The method and system also calculate
measures between members of social networks: social proximity and
trust level.
[0016] For a better understanding of the invention, the usages of
the following terms in the present disclosure are defined in a
non-limiting manner:
[0017] The term "Social network" as used herein in this
application, is defined as a directed graph of people, where each
edge A.fwdarw.B denotes that person A directly linked to person B
(e.g., knows him personally, communicates with him, etc). Each edge
is marked with a description of the nature of the acquaintance--how
A is connected to B, how long they know each other, etc.
[0018] The term "Social proximity" as used herein in this
application, is defined as a function over ordered pairs of people
in the virtual network, A and C, which measures the strength and
proximity of the connection between person A to person C as it can
be derived by the people and their links/connections in the virtual
community. There is no need for a direct connection from person A
to Person C
[0019] The term "Trust level" as used herein in this application,
is defined as a function over ordered pairs of people in a social
network, A and C, which measures the amount of belief person A can
have in person C's claims or judgment.
[0020] The term "Social path" as used herein in this application,
is defined as a path in a graph of social network: a series of
users A.sub.1.fwdarw.A.sub.2.fwdarw. . . . . An where each user
A.sub.i directly connected to user A.sub.i+1 (i.e. A.sub.i knows
user A.sub.i+1 personally).
[0021] The term "Best social paths" as used herein in this
application, is defined as a group of social paths between two
people in the net, A and C, such that the combined strength per
path of any two persons on these paths is the maximum possible in
that network.
[0022] The term "Voucher" as used herein in this application, is
defined as a person who can vouch for (tell about) another person,
whom he/she knows personally.
[0023] The term "Best vouchers" as used herein in this application,
is defined as a group of users that knows person C personally, such
that the information that person A can get about person C by
interrogating them is the maximum.
[0024] The term "Subjective network" as used herein in this
application, is defined as a sub-graph of the social network graph
that describes the network as a certain member (A) views it. The
subjective network contains members of the social network that are
socially closest to person A. It also contains values of the social
proximity, trust level and other relevant measures, between person
A and each other member in the network. A subjective network has a
certain "radius", which is the length of the longest path from user
A to a user in the network. For example, person A's subjective
network of radius 2 contains all friends and friends of friends of
person A, while A's subjective network of radius 3 contains friends
of friends of friends as well.
[0025] The term "social connectivity" as used herein in this
application, is defined as measure that represents the user's
connectivity to the network by taking into account the number of
connection he has, the strength of those connections, and,
recursively, the social connectivity of those he is connected
to.
[0026] The term "Social Layer" as used herein in this application,
is defined as a computing system that holds and processes
information of a unified virtual community. The system's
repositories hold data and/or references to data about people and
about the nature of connections among them. The data may be unified
across several sources.
[0027] The term "Greater Network" as used herein in this
application, is defined as a sub-graph of the social network graph
that describes the entire connected network that is connected to a
certain member (A). Any user B may be part of A's Greater network
if, and only if, there is at least one Social Path that connects A
with B.
[0028] The term "Social Proximity Service" as used herein in this
application, is defined as a service provided by the Social Layer
that calculates measures such as social proximity between users,
social paths.
[0029] The term "web based social environment" as used herein in
this application, comprises social networks, forums, professional
sites and other applications that hold social information.
[0030] According to some embodiments, one system uses a repository
of individuals, and a repository of social connections between
individuals which contains among others, the existence of
connection/s and the nature of the connection/s. For each member,
the system calculates the subjective network--the social network
that the member is part of and that is available for the member. In
that network, the system calculates subjective measures such as the
social proximity, trust level, best social paths, etc. to other
members of the network. The calculation uses among others,
graph-theory algorithms.
[0031] FIG. 1 is a high level schematic block diagram illustrating
a data processing system for calculating connectivity, social
proximity and trust level in social networks, according to some
embodiments of the invention. The system comprises a server 100
connected via a communication link 99 to a plurality of users 160
operatively associated with a social layer comprising at least one
web based social environment 140, to plurality of web based social
environments 140 and to a plurality of communication applications
150. Server 100 comprises an application 110, a graphical user
interface (GUI) 120 and a database 130. Server 100 receives data
relating to users 160, their profiles, connection and related data
in web based social environments 140 as well as large scale data
from web based social environments 140. Users 160 are further
prompted to fill questionnaires relating to their connections and
contacts in real life and in web based social environments 140.
Application 110 converts acquaintance data into a standard numeric
format. Application 110 converts all acquaintance data from all
sources into a standard numeric format that includes several
measures, including the trust level and the acquaintance level
between each two users that have any kind of direct connection
between them. The system uses a genuine conversion formula that
takes into account among others, the approximate number of
interactions between the two users, the duration of their
relationship, the nature of the interaction/s interaction, and
other information.
[0032] According to some embodiments of the invention, server 100
may comprise an online module 112 arranged to update the data and
related calculations substantially immediately after information
changes, and an offline module 114 arranged to analyze the data and
derived measures.
[0033] According to some embodiments of the invention, graphical
user interface 120 may be arranged to allow users to input
acquaintance data relating to them and other users.
[0034] According to some embodiments of the invention, application
110 may be further arranged to authenticate user identities, and to
rate user credibility in a context of electronic commerce from the
calculated measures in respect to other users.
[0035] According to some embodiments of the invention, server 100
may hold all relevant data or references to such data, and may
provide a service to web based social environments 140 or users
160. This service allows users 160 to get measurement regarding
another user which was previously unknown to them. Alternatively,
server 100 may comprise a social network website, with an added
value of showing social measures between members. Such social
network site can have a specific domain. In particular a dating
site based on this technology can be built to provide its users
with the added benefit of better trust between its members.
According to some embodiments of the invention, server 100 may
comprise a cell-phone application or a hardware component that
enables their owners to detect other, trustable people in their
proximity.
[0036] According to some embodiments of the invention,
communication applications 150 may comprise applications running on
mobile devices (such as cell phones), email applications, etc.
Communication applications 150 communicate with server 100 to
enable further data collection about the users and the people in
their proximity.
[0037] FIGS. 2 and 3 are high level flowcharts illustrating a
computer implemented method of calculating connectivity, social
proximity and trust level in social networks, according to some
embodiments of the invention. The method comprises the following
stages.
[0038] Collecting information related to users operatively
associated with a social layer comprising at least one web based
social environment (stage 200). Stage 200 may further comprise
allowing users in web based social environments to register upon
invitation from an inviter or upon self initiative, receiving
connection details from users and their inviters and collecting
information about the user, as well as receiving data from servers
of the web based social environments and as information from
predefined forms filled by any of the users.
[0039] Collecting acquaintance data (stage 210). Acquaintance data
may comprise user data from different web based social
environments, connections among users from different web based
social environments, data entered by other users in different web
based social environments, data from servers of the web based
social environments, as well as information from predefined forms
filled by any of the users.
[0040] Converting acquaintance data into a standard numeric format
(stage 220). The system converts all acquaintance data from all
sources into a standard numeric format that includes several
measures, including the trust level and the acquaintance level
between each two users that have any kind of direct connection
between them. The system uses a genuine conversion formula that
takes into account among others, the approximate number of
interactions between the two users, the duration of their
relationship, the nature of their interactions, and other
information.
[0041] Calculating measures for connected users (stage 230).
Measures may comprise social proximity, trust, paths and others.
Stage 230 applies for connected users who are directly connected.
The measures may be calculated in various ways among users, e.g.,
pair wise.
[0042] Generating connection graph, paths and subjective networks
relating to the users of the social layer (stage 240). Paths may be
generated in two phases--one at the data entry step--calculating
for every user a network of distance k; and the second one during
retrieval--calculating the network for the maximum desired
distance, M, based on the previous calculations of sub network of
radius k. in particular, the system and method may use in these
phases radiuses k and M where k=M/2 to simplify the calculation
process. According to some embodiments of the invention, stage 240
comprises calculating paths for a distance of k. The method expands
the network of every user to a radius of k, which can be smaller
then the maximum radius the method supports. For example, the
method may calculate the network for a user to a radius of 2: For
every ordered pair of users A and E such as there are users
B.sub.1, B.sub.2, . . . B.sub.n where A is connected to B.sub.i and
B.sub.i is connected with E, the method calculates the measures of
Trust and Social proximity between A and E based on the N paths
A.fwdarw.B.sub.i.fwdarw.E. The method weighs all paths to one
combined value, taking into account all weights of intermediate
connections
[0043] Adding information to the subjective networks (stage 250).
According to some embodiments of the invention, all the calculated
information is added to the subjective networks in the web based
social environment. The new information is incorporated into the
subjective networks of the relevant members.
[0044] Calculating measures for non connected users (stage 260).
Measures may comprise social proximity, trust, paths and others.
Stage 260 applies for users who are not connected (e.g., users in
different web based social environments that are each connected to
a user that is in all different web based social environments).
[0045] Generating a virtual network spanning different web based
social environments (stage 270), based on data coming from
different web based social environment to enable the calculation of
proximity between users who did not originally reside in the same
system.
[0046] Upon query--responding to the query by using the subjective
networks and caching calculated measures (stage 280). Each member
can query the database for measures relating him/her and other
members in the network. According to some embodiments of the
invention, to answer such queries, the system uses an online
calculation to create the subjective network of distance 4 for the
querying member. It does so by a genuine algorithm that combines
many subjective networks of distance 2. The subjective network of
distance 4 is then used to give the user an accurate and complete
answer to his/her query. According to some embodiments of the
invention, the calculation is split into two separate phases: phase
one calculated following the data entry ("offline") and, phase two
is calculated on data retrieval ("online"). This split balances
between a small and manageable data repository and a fast and
scalable response time for every request. Other external
applications or users using other applications can use the Social
Proximity service to obtain measures relating themselves and other
users in the network. This can be performed assuming that these
users have their relevant information and their network info stored
in the Social Layer. The calculated information can be cached for a
pre-determined period of time for reuse. The cache can be set to
void after some time. Calculating the user's network up to the
maximum radius of M can be cached together with all related
information such as its trust and proximity measures to every (or
some) of the users in that network. Subsequent queries that ask for
information that was recently cached can be retrieved from this
cache instead of being calculated again.
[0047] In the description above a radius of two was used in the
calculation of the sub-networks in the first phase, and a maximum
radius of four in the second phase. The invention does not limit
itself to these distances. The system and method may calculate the
measures for any maximum distance M, and to have a pre-calculation
step for any distance d (where d<=M). When using d and M where
M=2*d, the system and method may simplify the calculations. Using a
maximum distance of 4 and pre-calculation for a distance of 2 was
used in one of the implementation.
[0048] According to some embodiments of the invention, to register
into the database, a person may receive an invitation from existing
member/s who may know him/her from real life.
[0049] According to some embodiments of the invention, upon
registration, both the new member and the inviting member may fill
details about how the nature of connection between them. For
example, the type of acquaintance, how long they know each other,
etc.
[0050] According to some embodiments of the invention, the computer
implemented method further comprises assigning predefined
connection strengths to predefined relationships between users in
predefined organizations (stage 292). According to some embodiments
of the invention, a simple connection between users may be applied
if they both belong to the same organization, such as employees of
a specific company, students in the same academic institute, etc.
For each such generic connection a default connection strength will
be assigned to be used in calculating the various measures, A more
specific strength factor can be used when there is more information
regarding the connection within the organization, such as working
on the same department or same location, graduating from same
faculty or same year etc.
[0051] According to some embodiments of the invention, users can
allow the system to collect and add information to the database
also by retrieving their data, and data regarding their connections
and connected persons, from other media platforms including but not
limited to, social networking sites and applications thereof,
personal sites, websites, email applications, phones, etc.
[0052] According to some embodiments of the invention, data from
other repositories, including information regarding connectivity
between users, can also be obtained from other systems on a large
scale--that is, not on a per user basis, but rather a mass import
of connection information, in cases where the repository holders
wish to cooperate with us in order to obtain the benefits of our
services.
[0053] According to some embodiments of the invention, the
calculations may use persons whose data is not stored in the
repository, but rather the system and method may only have
information regarding their connection. For example, if persons A
and C are both registered in our database, and person A know a
person B, which is not registered in our database, and person C
knows B as well, the system and method may derive a path
A.fwdarw.B.fwdarw.C.
[0054] According to some embodiments of the invention, any path
A.sub.1.fwdarw.A.sub.2.fwdarw. . . . . An may not be valid and may
be excluded from the various calculation, if the corresponding path
A.sub.n.fwdarw.. . . A.sub.2.fwdarw.A.sub.1 does not exist.
According to some other embodiments of the invention, any such path
may get a smaller weight when used in calculating the various
measures.
[0055] According to some embodiments of the invention, the data
about connections of registered persons and about the persons they
connect with can be retrieved by crawling over public information
published by web based environments.
[0056] According to some embodiments of the invention, the method
may be repeated continuously, creating a database of members,
acquaintance information and subjective networks. The offline
calculation, described above, calculates subjective networks of
distance k. (for example, if the system and method may takes k=2,
for each user, the calculated subjective network includes his
friends and friends of friends only). This pre-calculation for a
partial distance (e.g., of two only and not for 4 or higher) is
done in order to save storage space and calculation time, since a
subjective network of distance 4 may include millions of users and
updating such a network may have scalability limitations.
[0057] According to some embodiments of the invention, the users
may add information and the method may get the information from
other sources. The method may get the data from some of the sources
and without the user's manual data entry. Data may be received in
an arbitrary order. Connection details can be added between any two
connected users. Connection info between users may be collected
either from user or from other sources, e.g. web based social
environments.
[0058] According to some embodiments of the invention, collecting
information related to users (stage 200) may comprise questioning
users for acquaintance data relating to other users (stage 288).
According to some embodiments of the invention, collecting
information related to users (stage 200) may comprise collecting
communication patterns of users as registered in communication
utilities (stage 290).
[0059] According to some embodiments of the invention, the input to
the system is data about the acquaintance of people with other
people, and the nature of their interaction The data can be
collected in several ways: The data can be provided manually by the
relevant people: The data may be entered in a human-friendly
form--a user has to say how he knows other users, and provide
additional information regarding their acquaintance: its duration,
frequency of meetings, quality of connection and other related
information that can help quantify the bond between the users; the
system transforms this information to numeric information.
According to some embodiments of the invention, data can be
retrieved from data stores that hold information about users'
relationship with other users, such as social networks, forums,
professional sites etc. Data can be retrieved from communication
utilities that hold information about the communication patterns of
a user with other people. This information include, list of
contacts, frequency and duration of communication, the context in
which these communications took place and the content passed in
these interactions.
[0060] According to some embodiments of the invention, the output
of the system for a specific person A, can be used to differentiate
between several levels of proximity and trust: (i) The highest
level includes all users B.sub.i for which the system could
calculate social proximity, trust, and/or other measures from A to
them. (ii) The second level includes all users C.sub.i which are
not in the first level and for which the system could verify that
they are in the same Greater Network as user A. (iii) The third
level includes all other users (i.e., not A and not in level 1 or
2). For every user D.sub.i on this level, user A may be advised to
be more cautious since their connection could not be verified.
[0061] According to some embodiments of the invention, the output
of the system is subjective--it is calculated personally for each
pair of users, so that person A gets the above mentioned measures
from his/her point of view. However, the trust level calculation
also takes into account objective information about each member of
the network. The system merges the subjective information with the
objective information.
[0062] According to some embodiments of the invention, the
objective information may include measurements which are not
limited to a specific user point of view. An example of such
measure can be the user's social connectivity.
[0063] According to some embodiments of the invention, the computer
implemented method may further comprise updating the collected
information and related calculations substantially immediately
after information changes (stage 286). According to some
embodiments of the invention, the calculations are done partially
"offline" and partially "online": The offline calculations are done
incrementally--when users change their social information related
to other users, only the relevant parts of the calculation are
re-executed. The online calculations are done when the information
is requested.
[0064] According to some embodiments of the invention, the
calculation can be performed for every pair in the combined data
repository. To calculate the measurements between two users, the
information regarding these users does not necessarily come from
one source. Moreover, the information about other users and their
connections, used to calculate the measurements and the paths, can
originate from different sources that were all aggregated into the
social layer.
[0065] According to some embodiments of the invention, the Social
Proximity Service may be used to validate or authenticate users in
various networks (social networks, websites and other
applications). The users may be using their nicknames or their
identifiers as they use in the respective web service and will use
the System which will hold their real information in its
repository, allowing it to find paths and other measures to
selected other members, in the same, or other websites, even if
those other members use nick-names or application identifiers
instead of their real name.
[0066] According to some embodiments of the invention, it supports
people in their decision making process of communicating via
digital media with other people. It also allows the representation
of people who are using the different means of the digital media in
a social layer (unified virtual community). The invention provides
indications that can be used by people to gauge other people
(including those who are not directly connected to each other). The
indications include, among others, Social proximity, Trust level,
best social paths, best vouchers, and others. The invention
provides outputs based on information that is gathered from the
digital media, including but not limited to: social networking
sites, websites, instant messaging applications, chat applications,
email applications, mobile applications, MMS, SMS, TV broadcasting
channels and all other communication platforms which can provide
related information.
[0067] According to some embodiments of the invention, the present
invention overcomes the problem of members of a social network
having no way of knowing whether other members in the network are
real people, fake profiles, or even criminals by allowing members
of a social network to have valuable information about other
members, before they even meet them. This enables members to feel
more secure in meeting new people for dating, business, etc.
Furthermore the present invention provides users with information
about their acquaintances stored in various locations, creating a
central repository that better reflects the user's real life
connectivity to all of his/her acquaintances and would allow users
to manage their connection data centrally. Finally having a
combined Social Layer allow users to locate their friends' friends
and rank them in one place, even if the information regarding their
friends, and their friend's friends reside originally in separate
unrelated systems.
[0068] According to some embodiments of the invention, main
advantages of the proposed invention are: (i) It is much more
difficult for a member to fake or alter artificially his/her trust
level, (ii) the input to the system relies on and reflects
real-life interactions and therefore is more user friendly, (iii)
the output of the system is much more accurate and complete, (iv) a
social proximity service also between people who are not directly
connected or know each other from first hand does not exist in
other solutions, (v) the network is updated and available in real
time, (vi) the information can span across social networks and
other data stores.
[0069] Specifically, according to some embodiments of the
invention, while in other systems, members can artificially
increase their trust level by inviting a lot of "fake friends", in
the disclosed system it is not possible, because trust is
calculated subjectively, so the fake trust of fake friends will
only affect the fake friends themselves, and not other members that
are not connected to them. While other systems ask users to fill an
arbitrary number that should mark their "trust level", while the
users don't have an objective way to calculate their "trust level"
to other users--the disclosed system asks the members questions in
human language, that they can answer objectively and clearly, e.g.
"how do you know person B?", "how often do you meet?" etc. These
questions are accompanied by a genuine formula that converts this
verbal information to numeric information, that can be further
processed by the social layer.
[0070] According to some embodiments of the invention, the accuracy
and completeness of the invention result from the following
characteristics: (i) The system and method use information gathered
from members up to distance 4 from the source user, which means
there are many possible paths (instead of using information from
direct connection only). (ii) The system and method try to take
into account all or most of the possible paths between the users
instead of a single path only. (iii) The system and method take
into account the nature of the connections between users and weight
them, and not just finds available paths.
[0071] According to some embodiments of the invention, the computer
implemented method may further comprise the following stages:
Authenticating user identities by crossing the collected
information from various sources (stage 282); and rating user
credibility in a context of electronic commerce from the calculated
measures in respect to other users (stage 284). According to some
embodiments of the invention, the system and method may further be
utilized to rate users in interactive systems, to enable better
trust in email communication and to enable trust between buyers and
sellers in e-commerce sites.
[0072] In the above description, an embodiment is an example or
implementation of the inventions. The various appearances of "one
embodiment," "an embodiment" or "some embodiments" do not
necessarily all refer to the same embodiments.
[0073] Although various features of the invention may be described
in the context of a single embodiment, the features may also be
provided separately or in any suitable combination. Conversely,
although the invention may be described herein in the context of
separate embodiments for clarity, the invention may also be
implemented in a single embodiment.
[0074] Reference in the specification to "some embodiments", "an
embodiment", "one embodiment" or "other embodiments" means that a
particular feature, structure, or characteristic described in
connection with the embodiments is included in at least some
embodiments, but not necessarily all embodiments, of the
inventions.
[0075] It is to be understood that the phraseology and terminology
employed herein is not to be construed as limiting and are for
descriptive purpose only.
[0076] The principles and uses of the teachings of the present
invention may be better understood with reference to the
accompanying description, figures and examples.
[0077] It is to be understood that the details set forth herein do
not construe a limitation to an application of the invention.
[0078] Furthermore, it is to be understood that the invention can
be carried out or practiced in various ways and that the invention
can be implemented in embodiments other than the ones outlined in
the description above.
[0079] It is to be understood that the terms "including",
"comprising", "consisting" and grammatical variants thereof do not
preclude the addition of one or more components, features, steps,
or integers or groups thereof and that the terms are to be
construed as specifying components, features, steps or
integers.
[0080] If the specification or claims refer to "an additional"
element, that does not preclude there being more than one of the
additional element.
[0081] It is to be understood that where the claims or
specification refer to "a" or "an" element, such reference is not
be construed that there is only one of that element.
[0082] It is to be understood that where the specification states
that a component, feature, structure, or characteristic "may",
"might", "can" or "could" be included, that particular component,
feature, structure, or characteristic is not required to be
included.
[0083] Where applicable, although state diagrams, flow diagrams or
both may be used to describe embodiments, the invention is not
limited to those diagrams or to the corresponding descriptions. For
example, flow need not move through each illustrated box or state,
or in exactly the same order as illustrated and described.
[0084] Methods of the present invention may be implemented by
performing or completing manually, automatically, or a combination
thereof, selected steps or tasks.
[0085] The term "method" may refer to manners, means, techniques
and procedures for accomplishing a given task including, but not
limited to, those manners, means, techniques and procedures either
known to, or readily developed from known manners, means,
techniques and procedures by practitioners of the art to which the
invention belongs.
[0086] The descriptions, examples, methods and materials presented
in the claims and the specification are not to be construed as
limiting but rather as illustrative only.
[0087] Meanings of technical and scientific terms used herein are
to be commonly understood as by one of ordinary skill in the art to
which the invention belongs, unless otherwise defined.
[0088] The present invention may be implemented in the testing or
practice with methods and materials equivalent or similar to those
described herein.
[0089] Any publications, including patents, patent applications and
articles, referenced or mentioned in this specification are herein
incorporated in their entirety into the specification, to the same
extent as if each individual publication was specifically and
individually indicated to be incorporated herein. In addition,
citation or identification of any reference in the description of
some embodiments of the invention shall not be construed as an
admission that such reference is available as prior art to the
present invention.
[0090] While the invention has been described with respect to a
limited number of embodiments, these should not be construed as
limitations on the scope of the invention, but rather as
exemplifications of some of the preferred embodiments. Other
possible variations, modifications, and applications are also
within the scope of the invention. Accordingly, the scope of the
invention should not be limited by what has thus far been
described, but by the appended claims and their legal
equivalents.
* * * * *